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Embedded Software for SoC - Grupo de Mecatrônica EESC/USP

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On-Chip Stochastic Communication 377<br />

the non<strong>de</strong>terministic nature of DSM faults. This suggests that a stochastic<br />

approach (<strong>de</strong>scribed next) is best suited to <strong>de</strong>al with such realities.<br />

4. STOCHASTIC COMMUNICATION<br />

The technique we call on-chip stochastic communication implements the NoC<br />

communication using a probabilistic broadcast algorithm [4]. The behavior<br />

of such an algorithm is similar to the spreading of a rumor within a large group<br />

of friends. Assume that, initially, only one person in the group knows the<br />

rumor. Upon learning the rumor, this person (the initiator) passes it to someone<br />

(confidant) chosen at random. At the next round, both the initiator and the<br />

confidant, if there is one, select in<strong>de</strong>pen<strong>de</strong>ntly of each other someone else to<br />

pass the rumor to. The process continues in the same fashion; namely,<br />

everyone in<strong>for</strong>med after t rounds passes the rumor at the (t + 1)th round to<br />

someone selected at random in<strong>de</strong>pen<strong>de</strong>ntly of all other past and present<br />

selections. Such a scheme is called gossip algorithm and is known to mo<strong>de</strong>l<br />

the spreading of an epi<strong>de</strong>mic in biology [16].<br />

Let I(t) be the number of people who have become aware of the rumor after<br />

t rounds (I(0) = 1) and let<br />

be the number of rounds until<br />

n people are in<strong>for</strong>med. We want to estimate in or<strong>de</strong>r to evaluate how fast<br />

the rumor is spread. A fundamental result states that:<br />

1<br />

with probability 1 [6]. There<strong>for</strong>e, after<br />

rounds (n represents the<br />

number of no<strong>de</strong>s) all the no<strong>de</strong>s have received the message with high<br />

probability (w.h.p.) [4]. For instance, in Figure 28-2, in less than 20 rounds<br />

as many as 1000 no<strong>de</strong>s can be reached. Conversely, after t rounds the number<br />

of people that have become aware of the rumor is an exponential function of<br />

t, so this algorithm spreads rumors exponentially fast.<br />

The analogy we make <strong>for</strong> the case of NoCs is that tiles are the “gossiping<br />

friends” and packets transmitted between them are the “rumors” (see Figure<br />

28-3). Since any friend in the original setup is able to gossip with anyone<br />

else in the group, the above analysis can be applied directly only to the case

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